//===- ArefLowering.cpp - Lower aref ops to target-specific -*- C++ -*-===//
// Aref 降低 Pass：将 aref 操作降低到目标特定的指令
//
// 支持三种目标：
// 1. CPU: aref -> 原子操作 + 自旋锁
// 2. SPIR-V: aref -> 工作组内存 + 屏障
// 3. NVIDIA PTX: aref -> TMA + 硬件屏障
//===----------------------------------------------------------------------===//

#include <string>
#include <vector>

namespace tawa {

// 目标平台枚举
enum class Target {
    CPU,
    SPIRV,
    NVPTX
};

// 占位：PTX 指令表示
struct PTXInstruction {
    std::string opcode;
    std::vector<std::string> operands;
};

//===----------------------------------------------------------------------===//
// CPU 后端降低
//===----------------------------------------------------------------------===//

// 将 aref.create 降低为栈分配 + 原子变量
std::vector<PTXInstruction> lowerCreateToCPU() {
    // 占位：实际需要生成 LLVM IR
    // %buffer = alloca [depth x element_type]
    // %empty_count = alloca atomic<i64>, align 8
    // store i64 %depth, atomic<i64>* %empty_count
    // %full_count = alloca atomic<i64>, align 8
    // store i64 0, atomic<i64>* %full_count
    return {};
}

// 将 aref.put 降低为 store + 原子递增
std::vector<PTXInstruction> lowerPutToCPU() {
    // 占位：实际需要生成 LLVM IR
    // ; 自旋等待空槽位
    // %empty = load atomic i64, atomic<i64>* %empty_count acquire
    // %has_empty = icmp sgt i64 %empty, 0
    // br i1 %has_empty, label %write, label %spin
    // 
    // write:
    // %slot = ... 计算槽位索引
    // store %data, %buffer[%slot]
    // %old_full = atomicrmw add atomic<i64>* %full_count, i64 1 release
    // %old_empty = atomicrmw sub atomic<i64>* %empty_count, i64 1 release
    return {};
}

// 将 aref.get 降低为自旋等待 + load
std::vector<PTXInstruction> lowerGetToCPU() {
    // 占位：实际需要生成 LLVM IR
    // ; 自旋等待满槽位
    // %full = load atomic i64, atomic<i64>* %full_count acquire
    // %has_full = icmp sgt i64 %full, 0
    // br i1 %has_full, label %read, label %spin
    // 
    // read:
    // %slot = ... 计算槽位索引
    // %data = load %buffer[%slot]
    // %old_full = atomicrmw sub atomic<i64>* %full_count, i64 1 acquire
    return {};
}

// 将 aref.consumed 降低为原子递增
std::vector<PTXInstruction> lowerConsumedToCPU() {
    // 占位：实际需要生成 LLVM IR
    // %old_empty = atomicrmw add atomic<i64>* %empty_count, i64 1 release
    return {};
}

//===----------------------------------------------------------------------===//
// SPIR-V 后端降低
//===----------------------------------------------------------------------===//

// 将 aref.create 降低为工作组内存分配 + 屏障
std::vector<PTXInstruction> lowerCreateToSPIRV() {
    // 占位：实际需要生成 SPIR-V
    // %buffer = OpVariable Workgroup [depth x element_type]
    // %empty_barrier = OpControlBarrier Workgroup Workgroup AcquireRelease
    // %full_barrier = OpControlBarrier Workgroup Workgroup AcquireRelease
    return {};
}

// 将 aref.put 降低为异步拷贝 + 屏障到达
std::vector<PTXInstruction> lowerPutToSPIRV() {
    // 占位：实际需要生成 SPIR-V
    // OpControlBarrier Workgroup Workgroup Acquire  ; 等待空屏障
    // OpCopyMemory %buffer %data
    // OpControlBarrier Workgroup Workgroup Release  ; 到达满屏障
    return {};
}

// 将 aref.get 降低为屏障等待 + 读取
std::vector<PTXInstruction> lowerGetToSPIRV() {
    // 占位：实际需要生成 SPIR-V
    // OpControlBarrier Workgroup Workgroup Acquire  ; 等待满屏障
    // %data = OpLoad %buffer
    return {};
}

// 将 aref.consumed 降低为屏障到达
std::vector<PTXInstruction> lowerConsumedToSPIRV() {
    // 占位：实际需要生成 SPIR-V
    // OpControlBarrier Workgroup Workgroup Release  ; 到达空屏障
    return {};
}

//===----------------------------------------------------------------------===//
// NVIDIA PTX 后端降低
//===----------------------------------------------------------------------===//

// 将 aref.create 降低为共享内存 + 硬件屏障
std::vector<PTXInstruction> lowerCreateToNVPTX() {
    std::vector<PTXInstruction> instructions;
    
    // 分配共享内存缓冲区
    instructions.push_back({"shmem.alloc", {"buffer_size"}});
    
    // 分配空屏障（初始计数 = depth）
    instructions.push_back({"mbarrier.init.shared.b64", {"empty_barrier", "depth"}});
    
    // 分配满屏障（初始计数 = 0）
    instructions.push_back({"mbarrier.init.shared.b64", {"full_barrier", "0"}});
    
    return instructions;
}

// 将 aref.put 降低为异步 TMA 加载
std::vector<PTXInstruction> lowerPutToNVPTX() {
    std::vector<PTXInstruction> instructions;
    
    // 等待空屏障
    instructions.push_back({"mbarrier.arrive.expect_tx.shared.b64", {"empty_barrier"}});
    instructions.push_back({"mbarrier.wait.shared.b64", {"empty_barrier"}});
    
    // 异步 TMA 加载
    instructions.push_back({"cp.async.bulk.tensor.2d.shared.global", 
                           {"buffer_addr", "data_addr", "tma_descriptor"}});
    
    // 到达满屏障
    instructions.push_back({"mbarrier.arrive.shared.b64", {"full_barrier"}});
    
    return instructions;
}

// 将 aref.get 降低为屏障等待 + 读取
std::vector<PTXInstruction> lowerGetToNVPTX() {
    std::vector<PTXInstruction> instructions;
    
    // 等待满屏障
    instructions.push_back({"mbarrier.wait.shared.b64", {"full_barrier"}});
    
    // 从共享内存读取数据
    instructions.push_back({"ld.shared.f32", {"result_reg", "buffer_addr"}});
    
    return instructions;
}

// 将 aref.consumed 降低为屏障到达
std::vector<PTXInstruction> lowerConsumedToNVPTX() {
    std::vector<PTXInstruction> instructions;
    
    // 到达空屏障
    instructions.push_back({"mbarrier.arrive.shared.b64", {"empty_barrier"}});
    
    return instructions;
}

//===----------------------------------------------------------------------===//
// 统一降低接口
//===----------------------------------------------------------------------===//

class ArefLoweringPass {
public:
    ArefLoweringPass(Target target) : target_(target) {}
    
    void runOnOperation() {
        // 占位：遍历所有 aref 操作并降低
        // for (auto op : module.getOps<tawa::ArefOp>()) {
        //     if (auto createOp = dyn_cast<tawa::CreateArefOp>(op)) {
        //         lowerCreate(createOp);
        //     } else if (auto putOp = dyn_cast<tawa::ArefPutOp>(op)) {
        //         lowerPut(putOp);
        //     } else if (auto getOp = dyn_cast<tawa::ArefGetOp>(op)) {
        //         lowerGet(getOp);
        //     } else if (auto consumedOp = dyn_cast<tawa::ArefConsumedOp>(op)) {
        //         lowerConsumed(consumedOp);
        //     }
        // }
    }
    
private:
    Target target_;
    
    void lowerCreate() {
        switch (target_) {
            case Target::CPU: lowerCreateToCPU(); break;
            case Target::SPIRV: lowerCreateToSPIRV(); break;
            case Target::NVPTX: lowerCreateToNVPTX(); break;
        }
    }
    
    void lowerPut() {
        switch (target_) {
            case Target::CPU: lowerPutToCPU(); break;
            case Target::SPIRV: lowerPutToSPIRV(); break;
            case Target::NVPTX: lowerPutToNVPTX(); break;
        }
    }
    
    void lowerGet() {
        switch (target_) {
            case Target::CPU: lowerGetToCPU(); break;
            case Target::SPIRV: lowerGetToSPIRV(); break;
            case Target::NVPTX: lowerGetToNVPTX(); break;
        }
    }
    
    void lowerConsumed() {
        switch (target_) {
            case Target::CPU: lowerConsumedToCPU(); break;
            case Target::SPIRV: lowerConsumedToSPIRV(); break;
            case Target::NVPTX: lowerConsumedToNVPTX(); break;
        }
    }
};

} // namespace tawa
